Changes in resting metabolic rate in an elderly German population: cross-sectional and longitudinal data

Resting metabolic rate in relation to incident disability and mobility decline among older adults: the modifying role of frailty

BACKGROUND

Alterations in resting metabolic rate (RMR), the largest component of daily total energy expenditure, with aging have been shown in various studies. However, little is known about the associations between RMR and health outcomes in later life.

AIMS

To analyze whether RMR is associated with incident disability and mobility decline in a 10-year longitudinal study, as well as the moderating role of frailty in these associations.

METHODS

Data from 298 older adults aged 70 and over from the Frailty and Dependence in Albacete (FRADEA) study in Spain were used, including a baseline measurement in 2007-2009 and a follow-up measurement 10 years later. RMR was measured by indirect calorimetry. Outcomes were incident disability in basic activities of daily living (BADL, Barthel Index), incident disability in instrumental ADL (IADL, Lawton index), and mobility decline (Functional Ambulation Categories scores). Fried's frailty phenotype was used as an indicator of frailty. Logistic regression analyses were conducted.

RESULTS

Fully adjusted and stratified analyses revealed that only in the pre-frail/frail group, a higher RMR was associated with a lower risk of incident BADL disability (OR = 0.47, 95% CI = 0.23-0.96, p = 0.037), incident IADL disability (OR = 0.39, 95% CI = 0.18-0.84, p = 0.017), and mobility decline (OR = 0.30, 95% CI = 0.14-0.64, p = 0.002).

CONCLUSIONS

To our knowledge, this is the first study looking at the associations between RMR and functional health using a longitudinal research design. The results suggest that RMR could be used as an early identifier of a specific resilient group within the pre-frail and frail older population, with a lower risk of further health decline.

Factors of Obesity and Metabolically Healthy Obesity in Asia

The East Asian region (China, Japan, and South Korea) is comprised of almost 1.5 billion people and recent industrialization has brought with it a pandemic of rising obesity, even in children. As these countries are rapidly aging and functioning at sub-replacement birthrates, the burgeoning costs of obesity-related care may threaten socialized healthcare systems and quality of life. However, a condition called metabolically healthy obesity (MHO) has been found to be without immediate cardiopulmonary or diabetic risk. Thus, maintenance of the MHO condition for the obese in East Asia could buffer the burden of long-term obesity care on medical systems and knowledge of the biochemical, genetic, and physiological milieu associated with it could also provide new targets for intervention. Diverse physiological, psychological, environmental, and social factors play a role in obesogenesis and the transition of MHO to a metabolically unhealthy obesity. This review will give a broad survey of the various causes of obesity and MHO, with special emphasis on the East Asian population and studies from that region.

Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women

Resting metabolic rate (RMR) depends on body fat-free mass (FFM) and fat mass (FM), whereas abdominal fat distribution is an aspect that has yet to be adequately studied. The objective of the present study was to analyze the influence of waist circumference (WC) in predicting RMR and propose a specific estimation equation for older Chilean women. This is an analytical cross-sectional study with a sample of 45 women between the ages of 60 and 85 years. Weight, height, body mass index (BMI), and WC were evaluated. RMR was measured by indirect calorimetry (IC) and %FM using the Siri equation. Adequacy (90% to 110%), overestimation (>110%), and underestimation (<90%) of the FAO/WHO/UNU, Harris−Benedict, Mifflin-St Jeor, and Carrasco equations, as well as those of the proposed equation, were evaluated in relation to RMR as measured by IC. Normal distribution was determined according to the Shapiro−Wilk test. The relationship of body composition and WC with RMR IC was analyzed by multiple linear regression analysis. The RMR IC was 1083.6 ± 171.9 kcal/day, which was significantly and positively correlated with FFM, body weight, WC, and FM and inversely correlated with age (p < 0.001). Among the investigated equations, our proposed equation showed the best adequacy and lowest overestimation. The predictive formulae that consider WC improve RMR prediction, thus preventing overestimation in older women.

Personalised Accelerometer Cut-point Prediction for Older Adults' Movement Behaviours using a Machine Learning approach

BACKGROUND AND OBJECTIVES

Body-worn accelerometers are the most popular method for objectively assessing physical activity in older adults. Many studies have developed generic accelerometer cut-points for defining activity intensity in metabolic equivalents for older adults. However, methodological diversity in current studies has led to a great deal of variation in the resulting cut-points, even when using data from the same accelerometer. In addition, the generic cut-point approach assumes that 'one size fits all' which is rarely the case in real life. This study proposes a machine learning method for personalising activity intensity cut-points for older adults.

METHODS

Firstly, raw accelerometry data was collected from 33 older adults who performed set activities whilst wearing two accelerometer devices: GENEActive (wrist worn) and ActiGraph (hip worn). ROC analysis was applied to generate personalised cut-point for each data sample based on a device. Four cut-points have been considered: Sensitivity optimised Sedentary Behaviour; Specificity optimised Moderate to Vigorous Physical Activity; Youden optimised Sedentary Behaviour; and Youden optimised Moderate to Vigorous Physical Activity. Then, an additive regression algorithm trained on biodata features, that concern the individual characteristics of participants, was used to predict the cut-points. As the model output is a numeric cut-point value (and not discrete), evaluation was based on two error metrics, Mean Absolute Error and Root Mean Square Error. Standard Error of estimation was also calculated to measure the accuracy of prediction (goodness of fit) and this was used for performance comparison between our approach and the state-of-the-art. Hold-out and 10-Fold cross validation methods were used for performance validation and comparison.

RESULTS

The results show that our personalised approach performed consistently better than the state-of-the-art with 10-Fold cross validation on all four cut-points considered for both devices. For the ActiGraph device, the Standard Error of estimation from our approach was lower by 0.33 (Youden optimised Sedentary Behaviour), 9.50 (Sensitivity optimised Sedentary Behaviour), 0.64 (Youden optimised Moderate to Vigorous Physical Activity) and 22.11 (Specificity optimised Moderate to Vigorous Physical Activity). Likewise, the Standard Error of estimation from our approach was lower for the GENEActiv device by 2.29 (Youden optimised Sedentary Behaviour), 41.65 (Sensitivity optimised Sedentary Behaviour), 4.31 (Youden optimised Moderate to Vigorous Physical Activity) and 347.15 (Specificity optimised Moderate to Vigorous Physical Activity).

CONCLUSIONS

personalised cut-point can be predicted without prior knowledge of accelerometry data. The results are very promising especially when we consider that our method predicts cut-points without prior knowledge of accelerometry data, unlike the state-of-the-art. More data is required to expand the scope of the experiments presented in this paper.

The effect of age and body mass index on energy expenditure of critically ill medical patients

Background

Data on the influence of age and body mass index (BMI) on energy metabolism of the critically ill are heterogeneous. Due to the increasingly aging critically ill population, investigation on age- and BMI-specific energy metabolism is relevant.

Methods

A total of 394 indirect calorimetry measurements were conducted on 348 critically ill adult medical patients, including 46 repeat measurements after 3.6 ± 4.3 days. Measured resting energy expenditure (MREE) was compared for age groups, BMI, and gender. Predicted energy expenditure (PEE) using the Penn State, Swinamer, and Ireton-Jones equations and the ACCP recommendations was also compared with MREE.

Results

The patients were 65.6 ± 14.5 years old. Their mean Acute Physiology and Chronic Health Evaluation II score was 27.6 ± 7.8. Mean BMI was 27.8 ± 8.4 kg/m², and 25.6% were obese. MREE adjusted for ideal body weight decreased with increasing age, while it increased with increasing BMI. Age, BMI, and gender are independent determinants of MREE after adjusting for clinical factors (R² = 0.34). All four prediction equations showed a proportional bias, with the Penn State equation performing acceptably. In 46 patients with repeat indirect calorimetry, there was no significant difference between the first and second MREE (p = 0.62).

Conclusions

Age, BMI, and gender are independent determinants of resting energy expenditure in critically ill adults. Variations between measured and predicted energy expenditure are considerable. Should prediction equations be used, their performance in the specific population should be taken into consideration. Repeat indirect calorimetry may not always be necessary. However, this may depend on the length of stay and the extent of stress.

Validity of One-Day Physical Activity Recall for Estimating Total Energy Expenditure in Elderly Residents at Long-Term Care Facilities: CLinical EValuation of Energy Requirements Study (CLEVER Study)

Malnutrition is a severe problem among elderly residents living in long-term care facilities. A simple and accurate estimation for total daily energy expenditure (TEE) is required in order to provide them with an adequate amount of food. The purpose of this study was to validate a physical activity assessment tool for estimating TEE among elderly residents. The data of 58 subjects aged 69-99 y were analyzed in this study. The one-day physical activity recall was filled out by facility staff for a typical day. TEE was measured by the doubly labeled water (DLW) method (TEE_DLW), and predicted by one-day physical activity recall using the basal metabolic rate (pTEE_BMR) and body weight (pTEE_BW). The TEE_DLW, pTEE_BMR and pTEE_BW were 1,129±196 kcal/d, 1,186±251 kcal/d and 1,326±236 kcal/d, respectively. In a regression model, body weight, movement means and sex explained 39.0% of the variance in the difference between pTEE_BMR and TEE_DLW (p<0.05). Percentage of fat mass, body weight, and Barthel Index except mobility explained 47.3% of the variance in the difference between pTEE_BW and TEE_DLW (p<0.05). The current results suggested that pTEE_BW is not recommended to estimate TEE because the error depends on body size, and pTEE_BMR was significantly correlated with TEE_DLW but also included systematic errors in elderly residents. In order to improve the accuracy of the present assessment to estimate TEE, it is necessary to establish a new equation of basal metabolic rate for elderly residents and consider sex and movement means to estimate TEE.

Validity of predictive equations for resting energy expenditure in Korean non-obese adults

BACKGROUND/OBJECTIVES

Indirect calorimetry is the gold-standard method for the measurement of resting energy expenditure. However, this method is time consuming, expensive, and requires highly trained personnel. To overcome these limitations, various predictive equations have been developed. The objective of this study was to assess the validity of predictive equations for resting energy expenditure (REE) in Korean non-obese adults.

SUBJECTS/METHODS

The present study involved 109 participants (54 men and 55 women) aged between 20 and 64 years. The REE was measured by indirect calorimetry. Nineteen REE equations were evaluated for validity, by comparing predicted and measured REE results. Predictive equation accuracy was assessed by determining percent bias, root mean squared prediction error (RMSE), and percentage of accurate predictions.

RESULTS

The measured REE was significantly higher in men than in women (P < 0.001), but the difference was not significant after adjusting for body weight (P > 0.05). The equation developed in this study had an accuracy rate of 71%, a bias of 0%, and an RMSE of 155 kcal/day. Among published equations, the FAOweight equation gave the highest accuracy rate (70%), along with a bias of -4.4% and an RMSE of 184 kcal/day.

CONCLUSIONS

The newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the FAOweight equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.

Adipokines may mediate the relationship between resting metabolic rates and bone mineral densities in obese women

The researchers sought to test the possible link between resting metabolic rate and bone mineral density through four adipokines. Participants with lower resting metabolic rate (RMR) per kilogram demonstrated higher total bone mineral density (BMD), total T-score, and total Z-score. Omentin-1 had a mediatory effect on the relationship between RMR/kg of body weight and bone parameters.

INTRODUCTION

The previous results of studies regarding the links between obesity and bone health are controversial. For this reason, the researchers sought to test the possible link between RMR and BMD through the following four adipokines: vaspin, retinol binding protein 4, angiopoietin-like 6 (ANGPL6), and omentin-1.

METHODS

We enrolled 312 obese Iranian women (30 ≤ body mass index <40) in this cross-sectional study. In order to examine the association of serum adipokine levels with RMR and BMD, the participants were grouped based on RMR per body weight. Body composition, dietary intake, bone mineral density, and resting metabolic rate were assessed in all participants. Serum adipokine levels were quantified by the enzyme-linked immunosorbent assay (ELISA) method.

RESULTS

Low levels of RMR/kg were strongly associated with higher weight, body mass index, fat mass, and visceral fat levels. In fact, participants with an RMR/kg of body weight <20 kcal/24 h/kg were more obese (p < 0.05). Another noteworthy finding was that participants with lower RMR/kg demonstrated higher total BMD, total T-score, and total Z-score. Our results showed that omentin-1 had a mediatory effect on the relationship between RMR per kilogram of body weight and bone parameters (p < 0.05). Nevertheless, other adipokines such as vaspin, retinol-binding protein 4 (RBP4), and ANGPL6 did not affect the relationship between RMR and BMD (p > 0.05).

CONCLUSIONS

The inhibitory effect of omentin-1 on TNF-alpha seems to be able to reduce the amount of circulating leptin as adipokine, affecting energy expenditure and improving bone loss induced by estrogen deficiency and controlled effect of RMR on BMD.

The Impact of Multimorbidity on Resting Metabolic Rate in Community-Dwelling Women over a Ten-Year Period: A Cross-Sectional and Longitudinal Study

OBJECTIVES

Ageing has been associated with increasing multimorbidity. This study investigated whether the number of diseases is a predictor of resting metabolic rate (RMR) and its long-term changes in community-dwelling elderly women.

SUBJECTS AND DESIGN

Cross-sectional and longitudinal data, obtained over ten years with repeated follow-ups, from 180 women aged 60 - 86 years and with a BMI of 18 - 43 kg/m2 at baseline were analyzed.

MEASUREMENTS

RMR was measured using indirect calorimetry and body composition by bioelectrical impedance analysis. Diagnosed diseases were assessed by a questionnaire comprising 23 disease categories. Subjects with 0 - 2 diseases were classified as relatively healthy and with > 2 diseases as multimorbid.

RESULTS

At baseline, relatively healthy (N = 75) and multimorbid (N = 105) women did not differ in RMR. During the ten-year follow-up, the median (range) number of diseases increased from 2 (0 - 2) to 4 (0 - 8) in relatively healthy and from 5 (3 - 11) to 7 (3 - 15) in multimorbid women. In the longitudinal analyses, only women who were multimorbid at baseline showed a significant increase in RMR of 31 kJ/d per additional disease (P = 0.015), adjusted for fat-free mass, fat mass, waist circumference and age.

CONCLUSION

Increasing multimorbidity in community-dwelling women is associated with an increase in RMR independently of body composition and age.

Gender- and Age-Specific REE and REE/FFM Distributions in Healthy Chinese Adults

Basic data on the resting energy expenditure (REE) of healthy populations are currently rare, especially for developing countries. The aims of the present study were to describe gender- and age-specific REE distributions and to evaluate the relationships among glycolipid metabolism, eating behaviors, and REE in healthy Chinese adults. This cross-sectional survey included 540 subjects (343 women and 197 men, 20–79 years old). REE was measured by indirect calorimetry and expressed as kcal/day/kg total body weight. The data were presented as the means and percentiles for REE and the REE to fat-free mass (FFM) ratio; differences were described by gender and age. Partial correlation analysis was used to analyze the correlations between REE, tertiles of REE/FFM, and glycolipid metabolism and eating behaviors. In this study, we confirmed a decline in REE with age in women (p = 0.000) and men (p = 0.000), and we found that men have a higher REE (p = 0.000) and lower REE/FFM (p = 0.021) than women. Furthermore, we observed no associations among glycolipid metabolism, eating behaviors, and REE in healthy Chinese adults. In conclusion, the results presented here may be useful to clinicians and nutritionists for comparing healthy and ill subjects and identifying changes in REE that are related to aging, malnutrition, and chronic diseases.

High resting metabolic rate among Amazonian forager-horticulturalists experiencing high pathogen burden

OBJECTIVES

Resting metabolic rate (RMR) reflects energetic costs of homeostasis and accounts for 60 to 75% of total energy expenditure (TEE). Lean mass and physical activity account for much RMR variability, but the impact of prolonged immune activation from infection on human RMR is unclear in naturalistic settings. We evaluate the effects of infection on mass-corrected RMR among Bolivian forager-horticulturalists, and assess whether RMR declines more slowly with age than in hygienic sedentary populations, as might be expected if older adults experience high pathogen burden.

MATERIALS AND METHODS

RMR was measured by indirect calorimetry (Fitmate MED, Cosmed) in 1,300 adults aged 20 to 90 and TEE was measured using doubly labeled water (n = 40). Immune biomarkers, clinical diagnoses, and anthropometrics were collected by the Tsimane Health and Life History Project.

RESULTS

Tsimane have higher RMR and TEE than people in sedentary industrialized populations. Tsimane RMR is 18 to 47% (women) and 22 to 40% (men) higher than expected using six standard prediction equations. Tsimane mass-corrected TEE is similarly elevated compared to Westerners. Elevated leukocytes and helminths are associated with excess RMR in multivariate regressions, and jointly result in a predicted excess RMR of 10 to 15%. After age 40, RMR declines by 69 kcal/decade (p < .0001). Controlling for lean mass and height accounts for 71% of age-related RMR decline, and adding indicators of infection minimally affects the age slope. The residual level of age-related decline from age 40 is 1.2% per decade.

CONCLUSION

High pathogen burden may lead to higher metabolic costs, which may be offset by smaller body mass or other energy-sparing mechanisms.

Age-Dependent Changes in Resting Energy Expenditure (REE): Insights from Detailed Body Composition Analysis in Normal and Overweight Healthy Caucasians

Age-related changes in organ and tissue masses may add to changes in the relationship between resting energy expenditure (REE) and fat free mass (FFM) in normal and overweight healthy Caucasians. Secondary analysis using cross-sectional data of 714 healthy normal and overweight Caucasian subjects (age 18–83 years) with comprehensive information on FFM, organ and tissue masses (as assessed by magnetic resonance imaging (MRI)), body density (as assessed by Air Displacement Plethysmography (ADP)) and hydration (as assessed by deuterium dilution (D₂O)) and REE (as assessed by indirect calorimetry). High metabolic rate organs (HMR) summarized brain, heart, liver and kidney masses. Ratios of HMR organs and muscle mass (MM) in relation to FFM were considered. REE was calculated (REEc) using organ and tissue masses times their specific metabolic rates. REE, FFM, specific metabolic rates, the REE-FFM relationship, HOMA, CRP, and thyroid hormone levels change with age. The age-related decrease in FFM explained 59.7% of decreases in REE. Mean residuals of the REE-FFM association were positive in young adults but became negative in older subjects. When compared to young adults, proportions of MM to FFM decreased with age, whereas contributions of liver and heart did not differ between age groups. HOMA, TSH and inflammation (plasma CRP-levels) explained 4.2%, 2.0% and 1.4% of the variance in the REE-FFM residuals, but age and plasma T3-levels had no effects. HMR to FFM and MM to FFM ratios together added 11.8% on to the variance of REE-FFM residuals. Differences between REE and REEc increased with age, suggesting age-related changes in specific metabolic rates of organs and tissues. This bias was partly explained by plasmaT3-levels. Age-related changes in REE are explained by (i) decreases in fat free mass; (ii) a decrease in the contributions of organ and muscle masses to FFM; and (iii) decreases in specific organ and tissue metabolic rates. Age-dependent changes in the REE-FFMassociation are explained by composition of FFM, inflammation and thyroid hormones.

Gender-Specific Associations in Age-Related Changes in Resting Energy Expenditure (REE) and MRI Measured Body Composition in Healthy Caucasians

BACKGROUND

The effect of gender as well as gender-specific changes of fat free mass (FFM) and its metabolic active components (muscle mass and organ masses [OMs]) and fat mass (FM) on age-related changes in resting energy expenditure (REE) are not well defined. We hypothesized that there are gender differences in (1) the age-specific onset of changes in detailed body composition (2); the onset of changes in body composition-REE associations with age.

METHODS

Using a cross-sectional magnetic resonance imaging database of 448 Caucasian participants (females and males) with comprehensive data on skeletal muscle (SM) mass, adipose tissue (AT), OMs, and REE.

RESULTS

We observed gender-specific differences in the onset of age-related changes in metabolic active components and REE. Declines in body composition and REE started earlier in females than in males for SM (29.4 vs 39.6 years), AT (38.2 vs 49.9 years), OM (34.7 vs 45.7 years), and REE (31.9 vs 36.8 years). The age-related decrease of AT was significantly higher in females than in males (-5.69kg/decade vs -0.59kg/decade). In females adjusted REEmFFM&FM (resting energy expenditure measured adjusted for FFM and FM) and REEmSM/OM/AT (resting energy expenditure measured adjusted for skeletal muscle and organ mass and adipose tissue) decreased by -145 kJ/d/decade and -604.8 kJ/d/ decade after the age of 35.2 respectively 34.3 years. SM was main determinant of REEm in females (R (2) = .67) and males (R (2) = .66) with remaining variance mainly explained by kidney mass (R (2) = .07) in females and liver mass (R (2) = .09) in males.

CONCLUSION

We concluded that gender affects the age-related changes in body composition as well as changes in body composition-REE relationship. This trial was registered at linicaltrials.gov as NCT01737034.

Energetics of Aging and Frailty: The FRADEA Study

BACKGROUND

Resting metabolic rate (RMR) and total daily energy expenditure (TDEE) decrease with aging, but it is not known whether frailty modulates this association. We hypothesize that RMR and TDEE values are similar between younger and older nonfrail older adults, whereas they are lower in older prefrail and frail compared with younger adults.

METHODS

A cross-sectional analysis of the FRADEA study, Albacete (Spain), including 402 participants (213 women) older than 70 years (mean age 76 years; range 70-91), was conducted. Estimated RMR (eRMR), oxygen consumption (VO2), expired volume (Ve), and respiratory frequency (RF) were determined using indirect calorimetry; TDEE was determined with the Calcumed instrument; and fat-free mass was determined by bioimpedanciometry. General linear models were used for analysis.

RESULTS

Mean TDEE was 1,889 (SD 470) kcal and eRMR was 1,071 (SD 323) kcal. Both TDEE (B = -24 kcal/day; 95% confidence interval: -35.4 to -14.2; p < .001) and eRMR (B= -15.8 kcal/day; 95% confidence interval: -23.1 to -8.5; p < .001) diminished linearly with age, with lower values in frail and prefrail participants. There was a strong trend between frailty and lower eRMR (F = 2.9; p = .058), with a modifying effect between age and frailty (F = 3.6; p = .002). eRMR in prefrail and frail participants were on average 160 and 114 kcal/day less than that in the nonfrail participants, respectively, and taken together, 154 kcal/day less (F = 5.4; p = .020). Frail and prefrail participants also presented lower Ve and VO2 values that were partially compensated by an RF increase.

CONCLUSION

Frailty status modulates the energy requirements of aging. Frail and prefrail older adults present lower eRMR than nonfrail adults.

Age-related changes in resting energy expenditure in normal weight, overweight and obese men and women

OBJECTIVES

Aging is associated with changes in resting energy expenditure (REE) and body composition. We investigated the association between age and changes in REE in men and women stratified by body mass index (BMI) categories (normal weight, overweight and obesity). We also examined whether the age-related decline in REE was explained by concomitant changes in body composition and lifestyle factors.

STUDY DESIGN

Cross-sectional.

MAIN OUTCOME MEASURES

3442 adult participants (age range: 18-81 y; men/women: 977/2465) were included. The BMI range was 18.5-60.2 kg/m(2). REE was measured by indirect calorimetry in fasting conditions and body composition by bioelectrical impedance. Regression models were used to evaluate age-related changes in REE in subjects stratified by sex and BMI. Models were adjusted for body composition (fat mass, fat free mass), smoking, disease count and physical activity.

RESULTS

In unadjusted models, the rate of decline in REE was highest in obese men (slope=-8.7±0.8 kcal/day/year) whereas the lowest rate of decline was observed in normal weight women (-2.9±0.3 kcal/day/year). Gender differences were observed for the age of onset of REE adaptive changes (i.e., not accounted by age related changes in body composition and lifestyle factors). In women, adaptive changes appeared to occur in middle-age (∼47 y) across all BMI groups whereas changes seemed to be delayed in obese men (∼54 y) compared to overweight (∼43 y) and normal weight (∼39 y) men.

CONCLUSIONS

Sex and BMI influenced the rate and degree of the age-related decline in REE. Critical age windows have been identified for the onset of putative mechanisms of energy adaptation. These findings require confirmation in prospective studies.

Energy Expenditure in Institutionalized Older Adults: Validation of SenseWear Mini

PURPOSE

Objective methods to quantify physical activity (PA) and predict energy expenditure (EE) are needed in the old and old-old. The aim of the present study was to evaluate the validity of EE estimates by the SenseWear Mini (SWMini) compared with indirect calorimetry during daily life activities in institutionalized older adults.

METHODS

Sixty nursing home residents (mean age = 85.5 ± 5.5 yr) wore the SWMini during rest (sitting quietly) and three activity tasks (walking, sitting/rising/walking, and moving objects). SWMini data were processed using software version 7.0. The criterion EE (kcal·min⁻¹) was estimated by a portable gas analyzer, Oxycon Mobile (OM).

RESULTS

The analyses revealed high correlations (rsitting = 0.68, ractivity tasks = 0.88) between EE estimated by OM and SWMini. EE increased between sitting periods and activity tasks for EE estimated by OM (mean difference = 61.5% ± 8.9%), as well as for EE estimated by SWMini (mean difference = 58.2% ± 7.4%) (P < 0.001). However, SWMini significantly underestimated EE, with an overall absolute percent error of 14.1% ± 7.9%. The largest absolute percent differences were observed during sitting periods compared with activity tasks (P < 0.05). Older age significantly reduced accuracy, explaining 12% of the variance in total percent error (β = 0.42, t = 2.84, P < 0.05).

CONCLUSIONS

The high percent error scores indicate that the SWMini is of limited value for quantifying EE in the old and old-old. The accuracy could be improved by developing accurate age- and activity-specific algorithms. On the other hand, the SWMini can be used as a suitable device for researchers interested in specific levels and patterns of PA and sedentary behavior.

Assessment of physical activity and energy expenditure: an overview of objective measures

The ability to assess energy expenditure (EE) and estimate physical activity (PA) in free-living individuals is extremely important in the global context of non-communicable diseases including malnutrition, overnutrition (obesity), and diabetes. It is also important to appreciate that PA and EE are different constructs with PA defined as any bodily movement that results in EE and accordingly, energy is expended as a result of PA. However, total energy expenditure, best assessed using the criterion doubly labeled water (DLW) technique, includes components in addition to physical activity energy expenditure, namely resting energy expenditure and the thermic effect of food. Given the large number of assessment techniques currently used to estimate PA in humans, it is imperative to understand the relative merits of each. The goal of this review is to provide information on the utility and limitations of a range of objective measures of PA and their relationship with EE. The measures discussed include those based on EE or oxygen uptake including DLW, activity energy expenditure, physical activity level, and metabolic equivalent; those based on heart rate monitoring and motion sensors; and because of their widespread use, selected subjective measures.

Best-fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations

Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.

Menopause and age-driven changes in blood level of fat- and water-soluble vitamins

OBJECTIVE

The purpose of this cross-sectional study was to assess the association of the menopausal transition with changes in vitamins.

METHODS

The study group comprised women aged 17-85 years from the Third National Health and Nutrition Examination Survey (NHANES), which was conducted between 1988 and 1994, and from the NHANES surveys conducted between 1999 and 2006. Menopausal status was defined using the time since the last period, < 2, 2-12, and > 12 months, for the pre-, peri-, and postmenopause, respectively. The data-cleaning technique employing serum follicle stimulating hormone activity resulted in pre-, peri- and postmenopausal samples encompassing the following age brackets: 17-50, 42-51, and 46-85 years. Statistical inferences were analyzed using non-parametric techniques.

RESULTS

Significant increases in vitamin A and vitamin E concentrations across all phases of the menopausal transition were observed. There was a gradual decrease in the vitamin C concentration across all stages of the menopause but a fairly stable concentration of vitamin B12. There was a statistically significant increase in vitamin D between the pre- and postmenopause. Body mass index correlated negatively with serum vitamin concentration in the pre- and postmenopause.

CONCLUSIONS

Vitamin A should be supplemented in postmenopausal women to decrease the risk of bone fracture. The daily diet should be supplemented with vitamin B12, to avoid possible neurological symptoms due to vitamin B12 deficiency, and with vitamin D to decrease the risk of developing secondary hyperparathyroidism. Due to an adverse influence on serum vitamin concentration, body mass index should be monitored in pre- and postmenopausal women.

Two variants located in the upstream enhancer region of human UCP1 gene affect gene expression and are correlated with human longevity

The brown fat specific UnCoupling Protein 1 (UCP1) is involved in thermogenesis, a process by which energy is dissipated as heat in response to cold stress and excess of caloric intake. Thermogenesis has potential implications for body mass control and cellular fat metabolism. In fact, in humans, the variability of the UCP1 gene is associated with obesity, fat gain and metabolism. Since regulation of metabolism is one of the key-pathways in lifespan extension, we tested the possible effects of UCP1 variability on survival. Two polymorphisms (A-3826G and C-3740A), falling in the upstream promoter region of UCP1, were analyzed in a sample of 910 subjects from southern Italy (475 women and 435 men; age range 40-109). By analyzing haplotype specific survival functions we found that the A-C haplotype favors survival in the elderly. Consistently, transfection experiments showed that the luciferase activity of the construct containing the A-C haplotype was significantly higher than that containing the G-A haplotype. Interestingly, the different UCP1 haplotypes responded differently to hormonal stimuli. The results we present suggest a correlation between the activity of UCP1 and human survival, indicating once again the intricacy of mechanisms involved in energy production, storage and consumption as the key to understanding human aging and longevity.